Matplotlib for data visualization in Raspberry Pi

Introduction

Matplotlib helps you turn numbers into pictures. Pictures make it easier to understand data quickly.

You want to see how temperatures change over a week.

You need to compare sales numbers for different products.

You want to show your sensor readings on a graph.

You want to find patterns in your data by looking at charts.

Syntax

Raspberry Pi

import matplotlib.pyplot as plt

plt.plot(x_values, y_values)
plt.title('Title of the graph')
plt.xlabel('X-axis label')
plt.ylabel('Y-axis label')
plt.show()

Use plt.plot() to draw lines or points on the graph.

plt.show() displays the graph window.

Examples

This draws a simple line graph connecting points (1,10), (2,20), (3,25), and (4,30).

Raspberry Pi

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.plot(x, y)
plt.show()

This draws a bar chart with bars at x positions and heights from y values.

Raspberry Pi

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.bar(x, y)
plt.show()

This draws points (dots) at the given x and y positions.

Raspberry Pi

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.scatter(x, y)
plt.show()

Sample Program

This program shows temperature changes over five days using a line graph with dots on each day.

Raspberry Pi

import matplotlib.pyplot as plt

# Data for days and temperature
x = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri']
y = [22, 24, 19, 23, 25]

plt.plot(x, y, marker='o')
plt.title('Temperature over a week')
plt.xlabel('Day')
plt.ylabel('Temperature (°C)')
plt.grid(True)
plt.show()

Important Notes

On Raspberry Pi, make sure you have Matplotlib installed using pip install matplotlib.

You can customize colors and styles by adding extra options to plotting functions.

Graphs help you spot trends and compare data easily.

Summary

Matplotlib turns data into easy-to-understand pictures.

You can draw lines, bars, or points to show your data.

Use titles and labels to explain what your graph shows.

Practice

1. What is the main purpose of using matplotlib in data science on a Raspberry Pi?

easy

A. To create visual pictures like charts from data

B. To store data in a database

C. To write data to a text file

D. To perform complex mathematical calculations

Solution

1. Step 1: Understand matplotlib's role

   Matplotlib is a tool used to turn data into visual charts and graphs.

2. Step 2: Compare options with matplotlib's function

   Only To create visual pictures like charts from data describes creating visual pictures, which matches matplotlib's purpose.

3. Final Answer:

   To create visual pictures like charts from data -> Option A

4. Quick Check:

   Matplotlib = Visual charts [OK]

Hint: Matplotlib = making charts from data [OK]

Common Mistakes:

• Confusing matplotlib with data storage tools
• Thinking matplotlib does calculations only
• Mixing up file writing with visualization

2. Which of the following is the correct way to import matplotlib's plotting module in Python on Raspberry Pi?

easy

A. import matplotlib as plt

B. import matplotlib.plot as plt

C. import matplotlib.plt as pyplot

D. import matplotlib.pyplot as plt

Solution

1. Step 1: Recall the standard import syntax

   The common way to import matplotlib's plotting is import matplotlib.pyplot as plt.

2. Step 2: Check each option for correctness

   Only import matplotlib.pyplot as plt matches the correct module name and alias.

3. Final Answer:

   import matplotlib.pyplot as plt -> Option D

4. Quick Check:

   Correct import = import matplotlib.pyplot as plt [OK]

Hint: Remember: pyplot, not plot or plt alone [OK]

Common Mistakes:

• Using wrong module names like 'plot' or 'plt' directly
• Mixing up alias names
• Typo in 'pyplot'

3. What will the following code display on a Raspberry Pi?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.title('Simple Line')
plt.show()

medium

A. A line chart with points (1,4), (2,5), (3,6) labeled axes and title

B. A scatter plot with points (1,4), (2,5), (3,6) without labels

C. A bar chart with bars at 1, 2, 3 heights 4, 5, 6

D. No plot will show because of syntax error

Solution

1. Step 1: Understand plt.plot() usage

   The plt.plot() function draws a line chart connecting points given by x and y lists.

2. Step 2: Check labels and title

   Labels for x and y axes and a title are set, so the chart will show them.

3. Final Answer:

   A line chart with points (1,4), (2,5), (3,6) labeled axes and title -> Option A

4. Quick Check:

   plt.plot() = line chart [OK]

Hint: plt.plot() makes line charts, not bars or scatter [OK]

Common Mistakes:

• Confusing plt.plot() with scatter or bar charts
• Ignoring axis labels and title
• Assuming syntax error without checking code

4. Identify the error in this code snippet for plotting a pie chart on Raspberry Pi:

import matplotlib.pyplot as plt
sizes = [10, 20, 30]
labels = ['A', 'B', 'C']
plt.pie(sizes, labels=labels)
plt.show()

medium

A. Missing plt.title() causes error

B. No error, code will run and show pie chart

C. sizes list must be numpy array, not list

D. plt.pie() requires colors argument

Solution

1. Step 1: Check pie chart function requirements

   The plt.pie() function accepts sizes as list and labels as list without error.

2. Step 2: Verify optional parameters

   Title and colors are optional; missing them does not cause errors.

3. Final Answer:

   No error, code will run and show pie chart -> Option B

4. Quick Check:

   plt.pie() works with lists and labels [OK]

Hint: Pie chart needs sizes and labels only, colors optional [OK]

Common Mistakes:

• Thinking title is mandatory
• Believing sizes must be numpy arrays
• Assuming colors argument is required

5. You want to plot a bar chart on Raspberry Pi showing sales for products A, B, and C with values 5, 7, and 3. Which code correctly creates this chart with labels and title?

hard

A. import matplotlib.pyplot as plt
products = ['A', 'B', 'C']
sales = [5, 7, 3]
plt.scatter(products, sales)
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales Bar Chart')
plt.show()

B. import matplotlib.pyplot as plt
products = ['A', 'B', 'C']
sales = [5, 7, 3]
plt.plot(products, sales)
plt.xlabel('Sales')
plt.ylabel('Products')
plt.title('Sales Bar Chart')
plt.show()

C. import matplotlib.pyplot as plt
products = ['A', 'B', 'C']
sales = [5, 7, 3]
plt.bar(products, sales)
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales Bar Chart')
plt.show()

D. import matplotlib.pyplot as plt
products = ['A', 'B', 'C']
sales = [5, 7, 3]
plt.pie(sales, labels=products)
plt.title('Sales Bar Chart')
plt.show()

Solution

1. Step 1: Identify correct chart type for sales data

   Bar charts show quantities per category, so plt.bar() is correct.

2. Step 2: Check axis labels and title

   Labels for products (x-axis) and sales (y-axis) match the data meaning.

3. Step 3: Verify other options

   import matplotlib.pyplot as plt products = ['A', 'B', 'C'] sales = [5, 7, 3] plt.plot(products, sales) plt.xlabel('Sales') plt.ylabel('Products') plt.title('Sales Bar Chart') plt.show() uses line plot with swapped labels, C uses scatter plot, D uses pie chart which is different visualization.

4. Final Answer:

   Code using plt.bar() with correct labels and title -> Option C

5. Quick Check:

   Bar chart = plt.bar() with correct labels [OK]

Hint: Use plt.bar() for bar charts, label axes clearly [OK]

Common Mistakes:

• Using plt.plot() or plt.scatter() for bar charts
• Swapping x and y axis labels
• Confusing pie chart with bar chart